greatexpectations - PySpark - ValueError: Unrecognized spark type: DecimalType(20,0) - pyspark

Question

I am trying to implement the to_be_of_type expectation mentioned here for DecimalType with precision and scale in PySpark.
However, I am getting following error while testing it.
{
"success": False,
"expectation_config": {
"expectation_type": "expect_column_values_to_be_of_type",
"meta": {},
"kwargs": {
"column": "project_id",
"type_": "DecimalType(20,0)",
"result_format": {
"result_format": "SUMMARY"
}
}
},
"meta": {},
"exception_info": {
"raised_exception": True,
"exception_message": "ValueError: Unrecognized spark type: DecimalType(20,0)",
"exception_traceback": "Traceback (most recent call last):\n File "/home/spark/.local/lib/python3.7/site-packages/great_expectations/dataset/sparkdf_dataset.py", line 1196, in expect_column_values_to_be_of_type\n success = issubclass(col_type, getattr(sparktypes, type_))\nAttributeError: module \"pyspark.sql.types\" has no attribute \"DecimalType(20,0)\"\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File "/home/spark/.local/lib/python3.7/site-packages/great_expectations/data_asset/data_asset.py", line 275, in wrapper\n return_obj = func(self, **evaluation_args)\n File "/home/spark/.local/lib/python3.7/site-packages/great_expectations/dataset/sparkdf_dataset.py", line 1201, in expect_column_values_to_be_of_type\n raise ValueError(f"Unrecognized spark type: {type_
}")\nValueError: Unrecognized spark type: DecimalType(20,0)\n"
},
"result": {}
},
Is there a possibility to validate the DecimalType with precision and scale values?
I am using GE version 0.14.12 and PySpark version 2.4.3.
Let me know if you need any further information.